Tensor networks provide extremely powerful tools for the study of complex classical and quantum many-body problems. Over the past two decades, the increment in the number of techniques and applications has been relentless, and especially the last ten years have seen an explosion of new ideas and results that may be overwhelming for the newcomer. This short review introduces the basic ideas, the best established methods, and some of the most significant algorithmic developments that are expanding the boundaries of the tensor network potential. The goal of this review is to help the reader not only appreciate the many possibilities offered by tensor networks but also find their way through state-of-the-art codes, their applicability, and some avenues of ongoing progress.

中文翻译：

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张量网络算法：路由图


张量网络为研究复杂的经典和量子多体问题提供了极其强大的工具。在过去的二十年里，技术和应用的数量不断增加，尤其是过去十年，新想法和结果的爆炸式增长可能会让新来者不知所措。这篇简短的评论介绍了基本思想、最佳成熟方法以及一些最重要的算法发展，这些发展正在扩大张量网络潜力的边界。这篇评论的目标是帮助读者不仅欣赏张量网络提供的许多可能性，而且通过最先进的代码、它们的适用性和一些持续进步的途径找到它们的方式。